Dynamic Approach and Testbed for Small and Medium Players Simulation in Smart Grid Environments

The Smart Grid environment allows the integration of resources of small and medium players through the use of Demand Response programs. Despite the clear advantages for the grid, the integration of consumers must be carefully done. This paper proposes a system which simulates small and medium players. The system is essential to produce tests and studies about the active participation of small and medium players in the Smart Grid environment. When comparing to similar systems, the advantages comprise the capability to deal with three types of loads – virtual, contextual and real. It can have several loads optimization modules and it can run in real time. The use of modules and the dynamic configuration of the player results in a system which can represent different players in an easy and independent way. This paper describes the system and all its capabilities.

Smart meters as a tool for energy efficiency

Gradually smart grids and smart meters are closer to the home consumers. Several countries has developed studies focused in the impacts arising from the introduction of these technologies and one of the main advantages are related to energy efficiency, observed through the awareness of the population on behalf of a more efficient consumption. These benefits are felt directly by consumers through the savings on electricity bills and also by the concessionaires through the minimization of losses in transmission and distribution, system stability, smaller loading during peak hours, among others. In this article two projects that demonstrate the potential energy savings through smart meters and smart grids are presented. The first performed in Korea, focusing on the installation of smart meters and the impact of use of user interfaces. The second performed in Portugal, focusing on the control of loads in a residence with distributed generation.

Quantum-based Particle Swarm Optimization Application to Studies of Aggregated Consumption Shifting and Generation Scheduling in Smart Grids

Demand response programs and models have been developed and implemented for an improved performance of electricity markets, taking full advantage of smart grids. Studying and addressing the consumers’ flexibility and network operation scenarios makes possible to design improved demand response models and programs. The methodology proposed in the present paper aims to address the definition of demand response programs that consider the demand shifting between periods, regarding the occurrence of multi-period demand response events. The optimization model focuses on minimizing the network and resources operation costs for a Virtual Power Player. Quantum Particle Swarm Optimization has been used in order to obtain the solutions for the optimization model that is applied to a large set of operation scenarios. The implemented case study illustrates the use of the proposed methodology to support the decisions of the Virtual Power Player in what concerns the duration of each demand response event.

A New Heuristic Providing an Effective Initial Solution for a Simulated Annealing approach to Energy Resource Scheduling in Smart Grids

An intensive use of dispersed energy resources is expected for future power systems, including distributed generation, especially based on renewable sources, and electric vehicles. The system operation methods and tool must be adapted to the increased complexity, especially the optimal resource scheduling problem. Therefore, the use of metaheuristics is required to obtain good solutions in a reasonable amount of time. This paper proposes two new heuristics, called naive electric vehicles charge and discharge allocation and generation tournament based on cost, developed to obtain an initial solution to be used in the energy resource scheduling methodology based on simulated annealing previously developed by the authors. The case study considers two scenarios with 1000 and 2000 electric vehicles connected in a distribution network. The proposed heuristics are compared with a deterministic approach and presenting a very small error concerning the objective function with a low execution time for the scenario with 2000 vehicles.

A calculus for modeling and analyzing conversations in service-oriented computing

Dissertação apresentada para a obtenção do Grau de Doutor em Informática pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Exploring distributed computing tools through data mining tasks

Harnessing idle PCs CPU cycles, storage space and other resources of networked computers to collaborative are mainly fixated on for all major grid computing research projects. Most of the university computers labs are occupied with the high puissant desktop PC nowadays. It is plausible to notice that most of the time machines are lying idle or wasting their computing power without utilizing in felicitous ways. However, for intricate quandaries and for analyzing astronomically immense amounts of data, sizably voluminous computational resources are required. For such quandaries, one may run the analysis algorithms in very puissant and expensive computers, which reduces the number of users that can afford such data analysis tasks. Instead of utilizing single expensive machines, distributed computing systems, offers the possibility of utilizing a set of much less expensive machines to do the same task. BOINC and Condor projects have been prosperously utilized for solving authentic scientific research works around the world at a low cost. In this work the main goal is to explore both distributed computing to implement, Condor and BOINC, and utilize their potency to harness the ideal PCs resources for the academic researchers to utilize in their research work. In this thesis, Data mining tasks have been performed in implementation of several machine learning algorithms on the distributed computing environment.

Pulseira inteligente para monitorização de funções vitais

A crescente utilização de dispositivos móveis com diferentes finalidades é uma realidade. Com estes dispositivos, o utilizador tem a necessidade de aceder e usar dados em tempo real provenientes de diversas fontes. Uma tendência acentuada passa pela incorporação destes dispositivos móveis no vestuário, designados por dispositivos wearable. Segundo a empresa IMS Research, o mercado deste tipo de dispositivos irá aumentar de 14 milhões de unidades registadas no presente ano (2013), para cerca de 171 milhões em 2016, sendo esta previsão conservadora, segundo o analista da IMS Research, Theo Ahadome [15]. A maioria dos dispositivos portáteis está atualmente projetada para questões de saúde, como a monitorização do nível de glicose e batimento cardíaco. O objetivo deste trabalho passa por definir e implementar um dispositivo wearable para aplicações de saúde com um conjunto de funcionalidades para monitorização dos sinais vitais do utilizador. Posteriormente esta base pode ser aplicada em cenários de aplicação distintos, em que todos os dispositivos comunicam entre si, e fazem o reencaminhamento da informação para onde mais interessar. Foi desenhado e implementado hardware e software, para a construção de aplicações capazes de realizar a monitorização do batimento cardíaco, temperatura e humidade corporal, deteção de quedas, qualidade do sono, e chamadas de emergência. Este trabalho aborda os diferentes cenários e aplicações da utilização deste dispositivo, invocando as necessidades específicas de cada situação, sendo estas necessidades trabalhadas e transformadas em características e especificações do sistema. A plataforma de hardware e software permite criar um ecossistema de aplicações, permitindo usar todas as infraestruturas do sistema desenvolvido em futuros cenários de aplicação.

The adoption of cloud computing by SMEs: identifying and coping with external factors.

Comunicação apresentada na CAPSI 2011 - 11ª Conferência da Associação Portuguesa de Sistemas de Informação – A Gestão de Informação na era da Cloud Computing, Lisboa, ISEG/IUL-ISCTE/, 19 a 21 de Outubro de 2011.

Sistema para a monitorização ativa com recurso ao cloud computing

O desenvolvimento de aplicações para dispositivos móveis já não é uma área recente, contudo continua a crescer a um ritmo veloz. É notório o avanço tecnológico dos últimos anos e a crescente popularidade destes dispositivos. Este avanço deve-se não só à grande evolução no que diz respeito às características destes dispositivos, mas também à possibilidade de criar aplicações inovadoras, práticas e passíveis de solucionar os problemas dos utilizadores em geral. Nesse sentido, as necessidades do quotidiano obrigam à implementação de soluções que satisfaçam os utilizadores, e nos dias de hoje, essa satisfação muitas vezes passa pelos dispositivos móveis, que já tem um papel fundamental na vida das pessoas. Atendendo ao aumento do número de raptos de crianças e à insegurança que se verifica nos dias de hoje, as quais dificultam a tarefa de todos os pais/cuidadores que procuraram manter as suas crianças a salvo, é relevante criar uma nova ferramenta capaz de os auxiliar nesta árdua tarefa. A partir desta realidade, e com vista a cumprir os aspetos acima mencionados, surge assim esta dissertação de mestrado. Esta aborda o estudo e implementação efetuados no sentido de desenvolver um sistema de monitorização de crianças. Assim, o objetivo deste projeto passa por desenvolver uma aplicação nativa para Android e um back-end, utilizando um servidor de base de dados NoSQL para o armazenamento da informação, aplicando os conceitos estudados e as tecnologias existentes. A solução tem como principais premissas: ser o mais user-friendly possível, a otimização, a escalabilidade para outras situações (outros tipos de monitorizações) e a aplicação das mais recentes tecnologias. Assim sendo, um dos estudos mais aprofundados nesta dissertação de mestrado está relacionado com as bases de dados NoSQL, dada a sua importância no projeto.

Smart city. O futuro já acontece

Águeda recebeu formalmente no passado mês de Março o Selo de SMART CITY assim como o prémio de inovação no que ao apoio á internacionalização das suas empresas diz respeito e ao empreendedorismo que sempre demostrou neste processo de desenvolvimento sustentável que já decorre no concelho á alguns anos. Mais do que uma SMART CITY, Águeda quer ser uma HUMAN SMART CITY onde a tecnologia é utilizada para servir as pessoas. Os pilares principais deste projeto assentam: • Governação • Mobilidade / Acessibilidades • Desenvolvimento Económico • Imagem de Marca • Ambiente / Sustentabilidade • Inovação

Estudo e integração de business models e a sua aplicação em smart-ups e projetos portugueses

Dissertação apresentada ao Instituto Superior de Contabilidade e Administração do Porto para obtenção do Grau de Mestre em Gestão das Organizações, Ramo Gestão de Empresas Orientador: Professor Doutor Eduardo Manuel Lopes de Sá e Silva Co-orientador: Mestre Maria de Fátima Mendes Monteiro

An intelligent clustering scheme for distributed intrusion detection in vehicular cloud computing

In recent years, vehicular cloud computing (VCC) has emerged as a new technology which is being used in wide range of applications in the area of multimedia-based healthcare applications. In VCC, vehicles act as the intelligent machines which can be used to collect and transfer the healthcare data to the local, or global sites for storage, and computation purposes, as vehicles are having comparatively limited storage and computation power for handling the multimedia files. However, due to the dynamic changes in topology, and lack of centralized monitoring points, this information can be altered, or misused. These security breaches can result in disastrous consequences such as-loss of life or financial frauds. Therefore, to address these issues, a learning automata-assisted distributive intrusion detection system is designed based on clustering. Although there exist a number of applications where the proposed scheme can be applied but, we have taken multimedia-based healthcare application for illustration of the proposed scheme. In the proposed scheme, learning automata (LA) are assumed to be stationed on the vehicles which take clustering decisions intelligently and select one of the members of the group as a cluster-head. The cluster-heads then assist in efficient storage and dissemination of information through a cloud-based infrastructure. To secure the proposed scheme from malicious activities, standard cryptographic technique is used in which the auotmaton learns from the environment and takes adaptive decisions for identification of any malicious activity in the network. A reward and penalty is given by the stochastic environment where an automaton performs its actions so that it updates its action probability vector after getting the reinforcement signal from the environment. The proposed scheme was evaluated using extensive simulations on ns-2 with SUMO. The results obtained indicate that the proposed scheme yields an improvement of 10 % in detection rate of malicious nodes when compared with the existing schemes.

Convergence of Smart Grid ICT architectures for the last mile

The evolution of the electrical grid into a smart grid, allowing user production, storage and exchange of energy, remote control of appliances, and in general optimizations over how the energy is managed and consumed, is also an evolution into a complex Information and Communication Technology (ICT) system. With the goal of promoting an integrated and interoperable smart grid, a number of organizations all over the world started uncoordinated standardization activities, which caused the emergence of a large number of incompatible architectures and standards. There are now new standardization activities which have the goal of organizing existing standards and produce best practices to choose the right approach(es) to be employed in specific smart grid designs. This paper follows the lead of NIST and ETSI/CEN/CENELEC approaches in trying to provide taxonomy of existing solutions; our contribution reviews and relates current ICT state-of-the-art, with the objective of forecasting future trends based on the orientation of current efforts and on relationships between them. The resulting taxonomy provides guidelines for further studies of the architectures, and highlights how the standards in the last mile of the smart grid are converging to common solutions to improve ICT infrastructure interoperability.

Haemoglobin smart plastic antibody material tailored with charged binding sites on silica nanoparticles: its application as an ionophore in potentiometric transduction

This work uses surface imprinting to design a novel smart plastic antibodymaterial (SPAM) for Haemoglobin (Hb). Charged binding sites are described here for the first time to tailor plastic antibody nanostructures for a large size protein such as Hb. Its application to design small, portable and low cost potentiometric devices is presented. The SPAM material was obtained by linking Hb to silica nanoparticles and allowing its ionic interaction with charged vinyl monomers. A neutral polymeric matrix was created around these and the imprinted protein removed. Additional materials were designed in parallel acting as a control: a neutral imprinted material (NSPAM), obtained by removing the charged monomers from the procedure, and the Non-Imprinted (NI) versions of SPAM and NSPAM by removing the template. SEM analysis confirmed the surface modification of the silica nanoparticles. All materials were mixed with PVC/plasticizer and applied as selective membranes in potentiometric transduction. Electromotive force (emf) variations were detected only for selective membranes having a lipophilic anionic additive in the membrane. The presence of Hb inside these membranes was evident and confirmed by FTIR, optical microscopy and Raman spectroscopy. The best performance was found for SPAM-based selective membranes with an anionic lipophilic additive, at pH 5. The limits of detection were 43.8 mg mL 1 and linear responses were obtained down to 83.8 mg mL 1, with an average cationic slope of +40 mV per decade. Good selectivity was also observed against other coexisting biomolecules. The analytical application was conducted successfully, showing accurate and precise results.

Graphene-based biomimetic materials targeting urine metabolite as potential cancer biomarker: Application over different conductive materials for potentiometric transduction

This work presents a novel surface Smart Polymer Antibody Material (SPAM) for Carnitine (CRT, a potential biomarker of ovarian cancer), tested for the first time as ionophore in potentiometric electrodes of unconventional configuration. The SPAM material consisted of a 3D polymeric network created by surface imprinting on graphene layers. The polymer was obtained by radical polymerization of (vinylbenzyl) trimethylammonium chloride and 4-styrenesulfonic acid (signaling the binding sites), and vinyl pivalate and ethylene glycol dimethacrylate (surroundings). Non-imprinted material (NIM) was prepared as control, by excluding the template from the procedure. These materials were then used to produce several plasticized PVC membranes, testing the relevance of including the SPAM as ionophore, and the need for a charged lipophilic additive. The membranes were casted over solid conductive supports of graphite or ITO/FTO. The effect of pH upon the potentiometric response was evaluated for different pHs (2-9) with different buffer compositions. Overall, the best performance was achieved for membranes with SPAM ionophore, having a cationic lipophilic additive and tested in HEPES (4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid) buffer, pH 5.1. Better slopes were achieved when the membrane was casted on conductive glass (-57.4 mV/decade), while the best detection limits were obtained for graphite-based conductive supports (3.6 × 10−5mol/L). Good selectivity was observed against BSA, ascorbic acid, glucose, creatinine and urea, tested for concentrations up to their normal physiologic levels in urine. The application of the devices to the analysis of spiked samples showed recoveries ranging from 91% (± 6.8%) to 118% (± 11.2%). Overall, the combination of the SPAM sensory material with a suitable selective membrane composition and electrode design has lead to a promising tool for point-of-care applications.